A radio system generally includes a transmitter that transmits information-carrying signals to a receiver. The transmitter includes a power amplifier that operates to amplify the signal to be transmitted to a power level that is sufficient to enable receipt of the signal by the receiver. Radio system transmitters are required to satisfy specifications for signal levels at frequencies other than the intended transmission frequencies. Some specifications are set by government regulatory bodies, while others are set by radio communications standards such as the Third Generation Partnership Project (3GPP) or IEEE 802.11. One specification, or requirement, is adjacent channel power, which is directly related to power amplifier linearity. Power amplifier linearity corresponds to an ability to reproduce an amplified version of the input signal. Also, power amplifiers are often described in terms of their efficiency, which is defined as some comparison between average transmit signal power and total average power required to generate the transmit signal power.
At a circuit level, power amplifier linearity may be achieved by biasing transistors in such a manner that the power amplifier operates in a linear fashion. However, doing so has a cost in terms of very low operating efficiency. As such, many modern power amplifiers are configured to operate at maximum efficiency, resulting in poor linearity, and use so-called “linearization” circuitry to correct non-linearity. Some exemplary power amplifiers that have high efficiency, but low linearity, are Class AB power amplifiers, Class B power amplifiers, Class C power amplifiers, Class F power amplifiers, Doherty power amplifiers, and Chireix power amplifiers.
Various linearization schemes have evolved having various trade-offs in terms of linearity, power dissipation, and versatility or robustness. These linearization schemes include, but are not limited to, analog predistortion, digital predistortion, feed-forward linearization, and feedback linearization. Predistortion linearization uses a predefined model of power amplifier non-linearity to generate an “opposite” nonlinear response that compensates for the non-linearity of the power amplifier. By amplifying the predistorted signal, the output of the power amplifier is as if the power amplifier were linear. The model utilized for predistortion needs to be designed to enable the predistortion to counteract the non-linear characteristics of the transistors forming the power amplifier. However, transistors are designed and fabricated using different technologies and therefore can exhibit drastically different characteristics.
Traditionally, there are two approaches to modeling the non-linear characteristic of the power amplifier, namely, a polynomial based approach and an artificial neural network model approach. The polynomial based approach includes the well-known Volterra series and its simplified versions, where the power series is the most basic form. The artificial neural network model approach uses artificial neural network modeling of the power amplifier. However, these approaches do not provide the desired performance in some situations. As such, there is a need for a high fidelity model for power amplifier predistortion.